1. Field of the Invention
This invention relates to a recurrent type fuzzy inference apparatus which monitors various industrial processes to infer a value of parameter suitable for the industrial process.
2. Prior Art
FIG. 1 is an explanatory view showing the operating principle of a conventional fuzzy inference apparatus, for example, shown in "Fuzzy System Theory and Fuzzy Control" appearing on pages 61 to 66 of "Labor Saving and Automation", November 1986 (by Kiyoji Asai). In FIG. 1, reference numerals 1 and 2 designate inference rules, and 3 and 4 designate characteristic variables to be inputted in the fuzzy inference apparatus, which are respectively the control error e and the rate of change Ue of the control error in the control system. Reference numerals 5 and 6 are membership functions of the first half of the rule 1, 7 the membership function of the second half of the rule 1, 8 and 9 the membership functions of the first half of the rule 2, and 10 the membership function of the latter half of the rule 2. Further, numeral 11 designates the membership function obtained by synthesizing the membership functions 7 and 10, and 12 the inference value obtained by taking the center of gravity out of the membership function 11, and in this example, it is outputted as a manipulated variable Uu from the fuzzy inference apparatus.
FIG. 2 is a block diagram showing one example of a conventional fuzzy inference apparatus on the basis of the operating principle as mentioned above. In FIG. 2, reference numeral 13 designates the weighting unit constituting means which evaluates the degree of matching of the first half from the inputted characteristic variables 3 and 4 with respect to the rules 1 and 2 to weight the membership function of the second half on the basis of the degree of matching, 14 the synthesizing unit constituting means for synthesizing the membership functions weighted by the weighting unit 13, and 15 the inference value deciding unit constituting means for deciding an inference value 12 from the membership function synthesized by the synthesizing unit 14 to output the same.
The operation will be described hereinafter. The rule 1 herein refers to the following: "If the characteristic variable 3 (control error e) is slightly deviated negatively and the characteristic variable 4 (the rate of change Ue of the control error) is slightly deviated positively, then make the inference value 12 (manipulated variable Uu) slightly deviated positively". A portion of the above stated rule "If . . . " is called the aforementioned first half, and a later portion is called the aforementioned second half. Accordingly, the membership function 5 of the first half of the rule 1 defines "aggregation of the control error slightly deviated negatively", and the membership function 6 defines "aggregation of the rate of change of the control error slightly deviated negatively", and the membership function 6 defines "aggregation of the rate of change of the control error slightly deviated positively".
Assume now that the actual value of the control error as the characteristic variable 3 inputted into the weighting means 13 is eo and the actual value of the rate of change of the control error as the characteristic variable 4 is Ue.sub.o, the degree that the value e.sub.o is "the control error slightly deviated negatively" is evaluated as "0.8" by the membership function 5, and the degree that the value Ue.sub.o is "the rate of change of the control error slightly deviated positively" is evaluated as "0.7" by the membership function 6. Out of these evaluated values, the lower value "0.7" is employed to constitute the degree of matching of the first half of the rule 1. The membership function 7 of the second half of the rule 1 has a meaning that "make the manipulated variable slightly deviated positively", the membership function 7 being weighted 0.7 times in accordance with the value of the degree of matching of the first half.
This is totally true for the rule 2. That is, the degree of matching of the first half is evaluated on the basis of the actual value e.sub.o of the control error of the inputted characteristic variable 3 and the actual value Ue.sub.o of the rate of change of the control error of the characteristic variable 4, and the membership function 10 is weighted 0.5 times on the basis of the value "0.5" of the degree of matching. The thus weighted membership functions 7 and 10 are inputted into and synthesized by the synthesizing means 14 to obtain the synthesized membership function 11. Furthermore, the synthesized membership function 11 is inputted into the inference value deciding means 15 for calculation of the center of gravity, as a consequence of which the manipulated variable Uu.sub.o is outputted as the inference value 12 from the fuzzy inference apparatus.
As described above, in the fuzzy inference apparatus, a plurality of rules simultaneously function whereby the weighting of the second half corresponding to the degree of matching of the first half is effected and the value balanced as a whole is outputted as the inference value.
Since the conventional fuzzy inference apparatus is constructed as described above, in the case where the characteristic variable (Si) which is the input of the fuzzy inference apparatus is normally Si=0 but only when a certain phenomenon occurs, 0&lt;Si.ltoreq.1, the inference is impossible for the normal case where Si=0. And there further involves a problem in that even if the inference could be made, the inference value would not be a continuous value and in addition, if a parameter to be inferred is constant or merely changed slowly so that its rate of change is near zero, it is not possible to obtain a convergent inference value.